Search result: Catalogue data in Spring Semester 2018

Computer Science Bachelor Information
Bachelor Studies (Programme Regulations 2016)
First Year Examinations
First Year Examination Block 2
NumberTitleTypeECTSHoursLecturers
401-0212-16LAnalysis I Information O7 credits4V + 2UE. Kowalski
AbstractReal and complex numbers, vectors, functions, limits, sequences, series, power series, differentiation and integration in one variable
ObjectiveReal and complex numbers, vectors, functions, limits, sequences, series, power series, differentiation and integration in one variable
ContentReal and complex numbers, vectors, functions, limits, sequences, series, power series, differentiation and integration in one variable
LiteratureMichael Struwe: Analysis für Informatik
Christian Blatter: Ingenieur-analysis
Tom Apostol: Mathematical Analysis
Teaching materials and further information is available through the course website (Link)
252-0028-00LDesign of Digital Circuits Information O7 credits4V + 2UO. Mutlu
AbstractThe class provides an introduction to the design of digital circuitry. The class covers the basics of the technical foundations of gates. An introduction to hardware description languages and their use in the design process follows.
ObjectiveThe class provides an introduction to the design of digital circuitry. The class covers the basics of the technical foundations of gates. An introduction to hardware description languages and their use in the design process follows.
ContentThe class provides an introduction to the design of digital circuitry. The class covers the basics of the technical foundations of gates. An introduction to hardware description languages and their use in the design process follows.
252-0029-00LParallel Programming Information O7 credits4V + 2UT. Hoefler, M. Vechev
AbstractIntroduction to parallel programming: deterministic and non-deterministic programs, models for parallel computation, synchronization, communication, and fairness.
ObjectiveThe student should learn how to write a correct parallel program, how to measure its efficiency, and how to reason about a parallel program. Student should become familiar with issues, problems, pitfalls, and solutions related to the construction of parallel programs. Labs provide an opportunity to gain experience with threads, libraries for thread management in modern programming lanugages (e.g., Java, C#) and with the execution of parallel programs on multi-processor/multi-core computers.
252-0030-00LAlgorithms and Probability Information O7 credits4V + 2UA. Steger, E. Welzl
AbstractFortsetzung der Vorlesung Algorithmen und Datenstrukturen des ersten Semesters. Es werden klassische Algorithmen aus verschiedenen Anwendungsbereichen vorgestellt. In die diskrete Wahrscheinlichkeitstheorie wird eingeführt und das Konzept randomisierter Algorithmen an verschiedenen Beispielen vorgestellt.
ObjectiveVerständnis des Entwurfs und der Analyse von Algorithmen. Grundlagen der diskreten Wahrscheinlichkeitstheorie und ihrer Anwendung in der Algorithmik.
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